---
title: "SES6003 Assessment 3 - Super Netball"
date: '`r format(Sys.time(), "%B %d, %Y")`'

output: 
  flexdashboard::flex_dashboard:
    theme: readable
    logo: Figures/super_netball_logo.png
    source_code: embed
    social: menu
    storyboard: true
---

## Aim of Analysis
The aim of the following analysis is to determine if teams that take more shots from ***Zone 2*** score more points than teams that do not.

## Step 1. Load The Required Packages

Before analysing the data the following packages will need to be loaded;

***here*** - constructs a path to the projects data file
 
***tidyverse*** - a set of packages designed to work in together, packages needed within tidyverse include ***dtplyr*** and ***ggplot2***
 
***knitr*** - provides a general purpose tool for generating reports

***plotly*** - creates interactive web graphics in conjunction with ggplot2
 
***viridis*** - colours graphs in a readable format for color blind individuals

***flexdashboard*** - publish RMarkdown to a HTML dashboard


```{r setup, include=FALSE}
# Load required packages
library(here)
library(tidyverse)
library(knitr)
library(plotly)
library(viridis)
library(flexdashboard)
library(DT)

# Load in the data
Dataset3_Assessment3 <- read.csv(here("Data/Dataset3_Assessment3.csv"))

#Create new dataframe
SummaryData_All <- Dataset3_Assessment3 %>%
group_by(Team, Statistic) %>%
summarise(Min = min(Total),
Max = max(Total),
Mean = mean(Total),
SD = sd(Total),
Sum = sum(Total))

# Isolate with filter
SummaryData_attempt_from_zone2 <-
filter(SummaryData_All, Statistic == "attempt_from_zone2")

# Isolate with filter
SummaryData_Points <-
filter(SummaryData_All, Statistic == "points")

```

## Step 2. Load the Data
Load the data by using the read.csv function and the ***here*** package.

### Figure 1. Attempts from Zone 2. 

```{r PlotAttempts}
# Boxplot Attempts with ggplot
PlotAttempts <- ggplot(SummaryData_attempt_from_zone2, aes(x = Statistic, y = Sum)) +
  geom_jitter(aes(colour = Team)) +
  scale_colour_viridis_d() +
  geom_boxplot(alpha = 0.3) +
  xlab("Attempts from Zone 2") +
  ylab("Sum of Shots Over Season") +
  theme_classic()

# Make the PlotAttempts interactive
ggplotly(PlotAttempts)
```

### Figure 2. Points. 

```{r PlotPoints}
# Boxplot Points with ggplot
PlotPoints <- ggplot(SummaryData_Points, aes(x = Statistic, y = Sum)) +
  geom_jitter(aes(colour = Team)) +
  scale_colour_viridis_d() +
  geom_boxplot(alpha = 0.3) +
  xlab("Points") +
  ylab("Sum of Points Over Season") +
  theme_classic()

# Make the PlotPoints interactive
ggplotly(PlotPoints)
```